A proposed java algorithm for default-recovery rate model

This paper presents a Proposed Java Algorithm for the Default-Recovery Rates (DRR) Model. The DRR Model is the extension to the Black-Scholes-Merton Model focusing on calculating the default and recovery rates of a firm. Default risk is one of the crucial risks in the risk management area that should be managed effectively. The world financial turmoil today will see more poor firms landing to defaults and bankruptcies. The probabilistic assessment of their financial growth would at least minimize the unfavorable impact. Although there are several efforts, instruments and methods used to manage the risk, it is said to be insufficient. To the best of our knowledge, there has been limited innovation in developing the default risk mathematical model into a java program. Therefore, through this study, default risk is predicted quantitatively using the Proposed Java Algorithm. The DRR Model has been integrated in the form of java algorithm and code. The Proposed Java Algorithm is implemented by calculating the default and recovery rates of a company and hence, predicting its level of default risk. It is found that the default risk is predicted high equivalent to the company poor financial performance. This shows that the default and recovery rates predicted by the DRR Model contain significant information on companies’ performance. In addition, the proposed java Algorithm can be one of the enhancements to the credit risk modeling field in producing a user-friendly application run by a java program.